by Braden Kelley
Recently several people have asked me whether or not artificial intelligence (AI) has a role to play innovation. One of the ways I’ve answered this question is by speaking about how artificial intelligence can be used to help test/disprove assumptions. Innovation always makes assumptions and often the success or failure of any innovation effort is determined by how well the team identifies the critical assumptions to test, those that if incorrectly assumed to be true could later derail the pursuit of innovation or waste limited innovation investment dollars.
But I thought it could be interesting to use AI to answer this question in more detail, leveraging my Eight I’s of Infinite Innovation framework to highlight how artificial intelligence could be used at each step of the continuous innovation journey.
Below you will find a detailed explanation of the Eight I’s of Infinite Innovation framework along with clearly called out contextual responses generated by Microsoft CoPilot detailing how AI could be used productively during that specific phase of the continuous innovation journey from prompts generated by me after uploading a PDF version of the original Eight I’s of Infinite Innovation article (see the link at the bottom).
Creating a Continuous Innovation Capability
To achieve sustainable success at innovation, you must work to embed a repeatable process and way of thinking within your organization, and this is why it is important to have a simple common language and guiding framework of infinite innovation that all employees can easily grasp. If innovation becomes too complex, or seems too difficult then people will stop pursuing it, or supporting it.
Some organizations try to achieve this simplicity, or to make the pursuit of innovation seem more attainable, by viewing innovation as a project-driven activity. But, a project approach to innovation will prevent it from ever becoming a way of life in your organization. Instead you must work to position innovation as something infinite, a pillar of the organization, something with its own quest for excellence – a professional practice to be committed to.
So, if we take a lot of the best practices of innovation excellence and mix them together with a few new ingredients, the result is a simple framework organizations can use to guide their pursuit of continuous innovation – the Eight I’s of Infinite Innovation. This framework anchors what is a very collaborative process. Here is the framework and some of the many points organizations must consider during each stage of the continuous process:
1. Inspiration
- Employees are constantly navigating an ever changing world both in their home context, and as they travel the world for business or pleasure, or even across various web pages in the browser of their PC, tablet, or smartphone.
- What do they see as they move through the world that inspires them and possibly the innovation efforts of the company?
- What do they see technology making possible soon that wasn’t possible before?
- The first time through we are looking for inspiration around what to do, the second time through we are looking to be inspired around how to do it.
- What inspiration do we find in the ideas that are selected for their implementation, illumination and/or installation?
How to leverage artificial innovation during the Inspiration phase (according to AI):
- AI can help employees find inspiration by analyzing vast amounts of data from various sources, such as social media, news articles, and industry reports. By identifying emerging trends and patterns, AI can provide insights into what is possible and inspire new ideas for innovation. Additionally, AI-powered tools can help employees visualize potential solutions and explore creative possibilities.
2. Investigation
- What can we learn from the various pieces of inspiration that employees come across?
- How do the isolated elements of inspiration collect and connect? Or do they?
- What customer insights are hidden in these pieces of inspiration?
- What jobs-to-be-done are most underserved and are worth digging deeper on?
- Which unmet customer needs that we see are worth trying to address?
- Which are the most promising opportunities, and which might be the most profitable?
How to leverage artificial innovation during the Inspiration phase (according to AI):
- AI can assist in the investigation phase by processing and analyzing large datasets to uncover hidden insights and customer needs. Machine learning algorithms can identify patterns and correlations that may not be immediately apparent to humans, helping organizations understand which opportunities are most promising and worth pursuing. AI can also automate the process of gathering and organizing information, making it easier for employees to focus on deeper analysis.
3. Ideation
- We don’t want to just get lots of ideas, we want to get lots of good ideas
- Insights and inspiration from first two stages increase relevance and depth of the ideas
- We must give people a way of sharing their ideas in a way that feels safe for them
- How can we best integrate online and offline ideation methods?
- How well have we communicated the kinds of innovation we seek?
- Have we trained our employees in a variety of creativity methods?
How to leverage artificial innovation during the Inspiration phase (according to AI):
- AI can enhance the ideation process by generating a wide range of ideas based on input from employees and external sources. Natural language processing (NLP) algorithms can analyze and categorize ideas, making it easier to identify the most relevant and promising ones. AI-powered collaboration tools can also facilitate brainstorming sessions, allowing employees to share and build on each other’s ideas in real-time, regardless of their physical location.
4. Iteration
- No idea emerges fully formed, so we must give people a tool that allows them to contribute ideas in a way that others can build on them and help uncover the potential fatal flaws of ideas so that they can be overcome
- We must prototype ideas and conduct experiments to validate assumptions and test potential stumbling blocks or unknowns to get learnings that we can use to make the idea and its prototype stronger
- Are we instrumenting for learning as we conduct each experiment?
How to leverage artificial innovation during the Inspiration phase (according to AI):
- AI can support the iteration phase by providing tools for rapid prototyping and experimentation. Machine learning models can simulate different scenarios and predict potential outcomes, helping teams identify and address potential flaws in their ideas. AI can also automate the process of collecting and analyzing feedback from experiments, enabling continuous improvement and refinement of prototypes.
5. Identification
- In what ways do we make it difficult for customers to unlock the potential value from this potentially innovative solution?
- What are the biggest potential barriers to adoption?
- What changes do we need to make from a financing, marketing, design, or sales perspective to make it easier for customers to access the value of this new solution?
- Which ideas are we best positioned to develop and bring to market?
- What resources do we lack to realize the promise of each idea?
- Based on all of the experiments, data, and markets, which ideas should we select?
How to leverage artificial innovation during the Inspiration phase (according to AI):
- AI can help organizations identify the most viable ideas by analyzing data from experiments, market research, and customer feedback. Predictive analytics can assess the potential success of different ideas and prioritize those with the highest likelihood of success. AI can also identify potential barriers to adoption and suggest strategies to overcome them, ensuring that innovative solutions are accessible and valuable to customers.
You’ll see in the framework that things loop back through inspiration again before proceeding to implementation. There are two main reasons why. First, if employees aren’t inspired by the ideas that you’ve selected to commercialize and some of the potential implementation issues you’ve identified, then you either have selected the wrong ideas or you’ve got the wrong employees. Second, at this intersection you might want to loop back through the first five stages though an implementation lens before actually starting to implement your ideas OR you may unlock a lot of inspiration and input from a wider internal audience to bring into the implementation stage.
6. Implementation
- What are the most effective and efficient ways to make, market, and sell this new solution?
- How long will it take us to develop the solution?
- Do we have access to the resources we will need to produce the solution?
- Are we strong in the channels of distribution that are most suitable for delivering this solution?
How to leverage artificial innovation during the Inspiration phase (according to AI):
- AI can streamline the implementation process by optimizing production, marketing, and sales strategies. AI-powered project management tools can help teams plan and execute tasks more efficiently, while machine learning algorithms can optimize supply chain and distribution processes. AI can also personalize marketing campaigns and sales approaches, ensuring that new solutions reach the right customers at the right time.
7. Illumination
- Is the need for the solution obvious to potential customers?
- Are we launching a new solution into an existing product or service category or are we creating a new category?
- Does this new solution fit under our existing brand umbrella and represent something that potential customers will trust us to sell to them?
- How much value translation do we need to do for potential customers to help them understand how this new solution fits into their lives and is a must-have?
- Do we need to merely explain this potential innovation to customers because it anchors to something that they already understand, or do we need to educate them on the value that it will add to their lives?
How to leverage artificial innovation during the Inspiration phase (according to AI):
- AI can enhance the illumination phase by helping organizations communicate the value of their innovations to potential customers. NLP algorithms can generate compelling marketing content and product descriptions, while sentiment analysis can gauge customer reactions and adjust messaging accordingly. AI can also identify key influencers and target them with personalized messages to amplify the reach of new solutions.
8. Installation
- How do we best make this new solution an accepted part of everyday life for a large number of people?
- How do we remove access barriers to make it easy as possible for people to adopt this new solution, and even tell their friends about it?
- How do we instrument for learning during the installation process to feedback new customer learnings back into the process for potential updates to the solution?
How to leverage artificial innovation during the Inspiration phase (according to AI):
- AI can facilitate the installation of new solutions by removing barriers to adoption and ensuring a seamless customer experience. AI-powered customer support tools can provide instant assistance and troubleshooting, while machine learning algorithms can personalize onboarding processes to meet individual customer needs. AI can also monitor usage patterns and gather feedback, enabling continuous improvement and updates to the solution.
Conclusion
The Eight I’s of Infinite Innovation framework is designed to be a continuous learning process, one without end as the outputs of one round become inputs for the next round. It’s also a relatively new guiding framework for organizations to use, so if you have thoughts on how to make it even better, please let me know in the comments. The framework is also ideally suited to power a wave of new organizational transformations that are coming as an increasing number of organizations (including Hallmark) begin to move from a product-centered organizational structure to a customer needs-centered organizational structure. The power of this new approach is that it focuses the organization on delivering the solutions that customers need as their needs continue to change, instead of focusing only on how to make a particular product (or set of products) better.
By leveraging AI at each stage of the innovation process, organizations can enhance their ability to generate, develop, and implement successful innovations.
So, as you move from the project approach that is preventing innovation from ever becoming a way of life in your organization, consider using the Eight I’s of Infinite Innovation to influence your organization’s mindset and to anchor your common language of innovation. The framework is great for guiding conversations, making your innovation outputs that much stronger, and will contribute to your quest for innovation excellence – it is even more powerful when you combine it with my Value Innovation Framework (found here). The two are like chocolate and peanut butter. They’re powerful tools when used separately, but even more powerful when used together.
Click to access this framework as a FREE scalable 11″x17″ PDF download
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People who upgrade to the Bronze Version of the Change Planning Toolkit™ will get access to my Innovation Planning Canvas™ which combines the Value Innovation Framework together with the Eight I’s of Infinite Innovation, allowing you to track the progress of each potential innovation on the three value innovation measures as you evolve any individual idea through this eight step process.
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